The Trellance Data Blog

Big Data and the CFO

Posted by Aaron Wang on Jun 10, 2013 11:01:18 AM

Big Data frequently is seen as only benefitting the marketing department. CFOs can also benefit from Big Data initiatives.

In a recent CFO Magazine article, author Phani Nagarjuna points out five ways CFOs can use Big Data to achieve their goals. While Nagarjuna writes about CFOs regardless of industry, I have sharpened the focus of his five points as they apply to credit union CFOs.

Risk Assessment

Credit union CFOs need to understand, quantify and predict risk. The NCUA mandates credit unions monitor seven standard risk categories and develop a total risk assessment plan. A big part of this effort depends on having sufficient data. Unfortunately, critical data can be locked up in separate silos which require extraordinary manual efforts to bring together to evaluate risk. Applying Big Data integration and analytics principles can greatly simplify this effort.

Growth & Innovation

The effort to drive improvements in a credit union’s financial health hopefully means lots of smart people are proposing lots of smart ways to accomplish the goal. Yet, how does the CFO quickly and accurately evaluate the financial merits of a numerous proposals? Armed with a more complete dataset than ever before, CFOs can use Big Data analytics methods to find the highest value actions.

Member Equity & Valuation

Forecasting the future financial picture of the credit union often depends on having a comprehensive view of member “walletshare”. Unfortunately, many credit unions have no good way to assess the complete picture of all a member’s accounts. Integrating all the data silos into a “member-centric” view, CFOs can more accurately estimate future financial trends.

Execution Efficiency

Evaluating the root causes of a credit union’s financial health is often a matter of determining “what’s working” and “what’s not working”. It sometimes requires digging down to specific transactions to find the causes of problems. Yet, it is typically not easy to “drill down” from summary numbers to more detailed data where the truth is hidden. Big Data analytics is geared for the kind of analysis that excels at finding these underlying causes.

Compliance & Regulation

Nagarjuna describes compliance and regulatory issues as “a time-consuming resource drain”. This is especially true for credit unions. As heavily regulated financial institutions, failure to adhere to NCUA regulations bears significant risk. By employing Big Data techniques, credit unions can greatly streamline their compliance and regulatory tasks by more easily managing large data volumes to deliver required information.

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Topics: Data Analytics, Leadership, Innovation